MLOps.community
471 episodes - English - Latest episode: 2 days ago - ★★★★★ - 17 ratingsWeekly talks and fireside chats about everything that has to do with the new space emerging around DevOps for Machine Learning aka MLOps aka Machine Learning Operations.
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Episodes
The Ops in MLOps - Process and People // Shalabh Chaudry // MLOps Podcast #146
February 21, 2023 15:17 - 59 minutes - 54.9 MBMLOps Coffee Sessions #146 with Shalabh Chaudry, The Ops in MLOps - Process and People co-hosted by Abi Aryan. // Abstract Shalabh talks through their newfound appreciation for the MLOps perspective from a customer success standpoint. Shalabh's emphasis on setting realistic expectations and ensuring the delivery of promised value adds is particularly valuable. Generally, this episode provides a unique and insightful perspective on MLOps from the lens of customer success. // Bio Sh...
Griffin, ML Platform at Instacart // Sahil Khanna // MLOps Podcast #145
February 14, 2023 11:20 - 45 minutes - 42.6 MBMLOps Coffee Sessions #145 with Sahil Khanna, Griffin, ML platform at Instacart co-hosted by Mike Del Balso. // Abstract The conversation revolves around the journey of Instacart in implementing machine learning, starting from batch processing to real-time processing. The speaker highlights the importance of real-time processing for businesses and the relevance of Instacart's journey to other machine learning teams. Sahil emphasizes the soft factors, such as staying customer-focused a...
Non-traditional Career Paths in MLOps // Matthew Dombrowski // MLOps Podcast #144
February 07, 2023 16:14 - 48 minutes - 44.6 MBMLOps Coffee Sessions #144 with Matthew Dombrowski, Non-traditional Career Paths in MLOps co-hosted by Mihail Eric. // Abstract Let's explore the different aspects of ML and data roles and the variety of responsibilities each role entails! This conversation emphasizes the need for understanding the unique insights each role provides and the similarities in responsibilities and soft skills that are required across different roles. This episode also highlights the significance of stakeh...
Investing in the Next Generation of AI & ML // Jill Chase & Manmeet Gujral // MLOps Podcast #143
January 31, 2023 13:27 - 41 minutes - 38.1 MBMLOps Coffee Sessions #143 with Jill Chase & Manmeet Gujral, Investing in the Next Generation of AI & ML. // Abstract Investors are currently focusing on developer tooling and the foundational AI model movement, as they have seen explosive growth in this area. This podcast explores the impact of foundational models on investment thesis and the future of machine learning operations. The discussion also touches on the idea of generative AI and large language models, and their potential impa...
Approaches to Fairness and XAI // Murtuza Shergadwala // MLOps Podcast #142
January 24, 2023 13:24 - 39 minutes - 36.3 MBMLOps Coffee Sessions #142 with Murtuza Shergadwala, Approaches to Fairness and XAI co-hosted by Abi Aryan. This episode is sponsored by Fiddler AI. // Abstract The field of Explainable Artificial Intelligence (XAI) is continuously evolving, with an increasing focus on providing model-centric explanations in a human-centric manner. However, better frameworks and training for users are needed to fully utilize the potential of XAI tools. Additionally, there is a discrepancy in the approac...
Airflow Sucks for MLOps // Stephen Bailey // MLOps Podcast #141
January 17, 2023 14:08 - 51 minutes - 47.9 MBMLOps Coffee Sessions #141 with Stephen Bailey, Airflow Sucks for MLOps co-hosted by Joe Reis. // Abstract Stephen discusses his experience working with data platforms, particularly the challenges of training and sharing knowledge among different stakeholders. This talk highlights the importance of having clear priorities and a sense of practicality and mentions the use of modular job design and data classification to make it easier for end users to understand which data to use. Stephe...
Updated The Evolution of ML Infrastructure // Sakib Dadi // MLOps Podcast #140
January 10, 2023 19:24 - 51 minutes - 47.8 MBMLOps Coffee Sessions #140 with Sakib Dadi, The Evolution of ML Infrastructure sponsored by Wallaroo. // Abstract The toolkit and infrastructure empowering machine learning practitioners are advancing as ML adoption accelerates. We'll go through the current landscape of ML tooling, startups, and new projects from an investor's perspective. // Bio Sakib is a vice president in the San Francisco office where he primarily focuses on early-stage investments in developer platforms, data infr...
Foundational Models are the Future but... with Alex Ratner CEO of Snorkel AI // MLOps Podcast #139
January 03, 2023 13:14 - 52 minutes - 48.5 MBMLOps Coffee Sessions #139 with Alex Ratner, Putting Foundation Models to Use for the Enterprise co-hosted by Abi Aryan sponsored by Snorkel AI. // Abstract Foundation models are rightfully being compared to other game-changing industrial advances like steam engines or electric motors. They’re core to the transition of AI from a bespoke, less predictable science to an industrialized, democratized practice. Before they can achieve this impact, however, we need to bridge the cost, quality, a...
Explainability in the MLOps Cycle // Dattaraj Rao // MLOps Podcast #138
December 27, 2022 13:15 - 41 minutes - 38.1 MBMLOps Coffee Sessions #138 with Dattaraj Rao, Explainability in the MLOps Cycle co-hosted by Vishnu Rachakonda. // Abstract When it comes to Dattaraj's interest, you'll hear about his top 3 areas in Machine Learning. What he sees as up and coming, what he's investing his company's time into and where he invests his own time. Learn more about rule-based systems, deploying rule-based systems , and how to incorporate systems into more systems. there is no difference between ML systems and de...
Machine Learning Operations — What is it and Why Do We Need It? // Niklas Kühl // MLOps Podcast #137
December 20, 2022 12:38 - 59 minutes - 55 MBMLOps Coffee Sessions #137 with Niklas Kühl, Machine Learning Operations — What is it and Why Do We Need It? co-hosted by Abi Aryan. // Abstract The final goal of all industrial machine learning (ML) projects is to develop ML products and rapidly bring them into production. However, it is highly challenging to automate and operationalize ML products and thus many ML endeavors fail to deliver on their expectations. The paradigm of Machine Learning Operations (MLOps) addresses this issu...
Systems Engineer Navigating the World of ML // Andrew Dye // MLOps Podcast #136 video
December 13, 2022 12:26 - 39 minutes - 36.6 MBMLOps Coffee Sessions #136 with Andrew Dye, Systems Engineer Navigating the World of ML co-hosted by David Aponte. // Abstract We don't hear that much about working at a very low level on this podcast but they are still very valid. Andrew is able to give us his take on why and what you need to keep in mind when you are working at these low levels and why it is very important when you are a Machine Learning Engineer and how the two can play together nicely. Most MLOps teams are formed usin...
Systems Engineer Navigating the World of ML // Andrew Dye // MLOps Podcast #136
December 13, 2022 12:26 - 39 minutes - 36.6 MBMLOps Coffee Sessions #136 with Andrew Dye, Systems Engineer Navigating the World of ML co-hosted by David Aponte. // Abstract We don't hear that much about working at a very low level on this podcast but they are still very valid. Andrew is able to give us his take on why and what you need to keep in mind when you are working at these low levels and why it is very important when you are a Machine Learning Engineer and how the two can play together nicely. Most MLOps teams are formed usin...
"Real-Time" ML: Features and Inference // Sasha Ovsankin and Rupesh Gupta // MLOps Podcast #135
December 09, 2022 11:04 - 52 minutes - 48.3 MBMLOps Coffee Sessions #135 with Sasha Ovsankin and Rupesh Gupta, Real-time Machine Learning: Features and Inference co-hosted by Skylar Payne. // Abstract Moving from batch/offline Machine Learning to more interactive "near" real-time requires knowledge, team, planning, and effort. We discuss what it means to do real-time inference and near-real-time features when to do this move, what tools to use, and what steps to take. // Bio Sasha Ovsankin Sasha is currently a Tech Lead of Machi...
"Real-Time" ML: Features and Inference // Sasha Ovsankin and Rupesh Gupta // MLOps Podcast #134
December 09, 2022 11:04 - 52 minutes - 48.3 MBMLOps Coffee Sessions #134 with Sasha Ovsankin and Rupesh Gupta, Real-time Machine Learning: Features and Inference co-hosted by Skylar Payne. // Abstract Moving from batch/offline Machine Learning to more interactive "near" real-time requires knowledge, team, planning, and effort. We discuss what it means to do real-time inference and near-real-time features when to do this move, what tools to use, and what steps to take. // Bio Sasha Ovsankin Sasha is currently a Tech Lead of Machi...
Building Threat Detection Systems: An MLE's Perspective // Jeremy Jordan // MLOps Podcast #134
December 06, 2022 13:55 - 50 minutes - 46.7 MBMLOps Coffee Sessions #134 with Jeremy Thomas Jordan, Building Threat Detection Systems: An MLE's Perspective co-hosted by Vishnu Rachakonda. // Abstract There is a clear pattern that we have been seeing with some of these greats in MLOps. So many use writing as a forcing function to learn about where they have holes in their understanding of something. If you are not writing, this episode is important as to why writing is important for your own development. Jeremy goes into writing in...
Real-time Machine Learning with Chip Huyen // Chip Huyen // MLOps Coffee Sessions #133
November 22, 2022 13:39 - 58 minutes - 53.7 MBMLOps Coffee Sessions #133 {Podcast BTS} with Chip Huyen, Real-time Machine Learning with Chip Huyen co-hosted by Vishnu Rachakonda. // Abstract Forcing functions and how you can supercharge your learning by putting yourself into a situation where you know you either have a responsibility to others to learn or accountability on you so you have to learn. It's not that hard when you think about streaming machine learning. It's not that big of a mental barrier to cross. It is simple in th...
Real-time Machine Learning with Chip Huyen // MLOps Coffee Sessions #133
November 22, 2022 13:39 - 58 minutes - 53.7 MBMLOps Coffee Sessions #133 {Podcast BTS} with Chip Huyen, Real-time Machine Learning with Chip Huyen co-hosted by Vishnu Rachakonda. // Abstract Forcing functions and how you can supercharge your learning by putting yourself into a situation where you know you either have a responsibility to others to learn or accountability on you so you have to learn. It's not that hard when you think about streaming machine learning. It's not that big of a mental barrier to cross. It is simple in th...
What is Data / ML Like on League? // Ian Schweer // MLOps Coffee Sessions #132
November 15, 2022 12:43 - 1 hour - 55.8 MBMLOps Coffee Sessions #132 {Podcast BTS} with Ian Schweer, What is Data / ML Like on League? co-hosted by Skylar Payne. // Abstract If you're not an avid gamer yourself, you have never really seen how ML might be used in the gaming space. It's so interesting to see the things that are different like full stories of players' games from start to finish. // Bio On the surface, Ian is an excellent developer who gets things done. Underneath, he is much more. Ian is a reliable and trustwor...
Let's Continue Bundling into the Database // Ethan Rosenthal // MLOps Coffee Sessions #131
November 08, 2022 12:47 - 51 minutes - 47.6 MBMLOps Coffee Sessions #131 {Podcast BTS} with Ethan Rosenthal, Let's Continue Bundling into the Database co-hosted by Mike Del Balso. // Abstract The relationship between ML Engineers and Product Managers is something that we don't talk about enough. We've got to get this right. If we don't get this right, either you're not focusing on the business problems in the right way or the Product Managers are not going to understand the tech appropriately to help make the right decisions. // Bio...
MLOps for Ad Platforms // Andrew Yates // MLOps Coffee Sessions #130
October 31, 2022 12:19 - 44 minutes - 40.9 MBMLOps Coffee Sessions #130 {Podcast BTS} with Andrew Yates, Adversarial MLOps on Other People's Money: Lessons Learned from Ad Tech co-hosted by Abi Aryan. // Abstract Design ML to be components in a larger system with stable interfaces is not tracible to monitor the entire stack as a black box. You need intermediate ground-truth signals. Ads are designed in this way. You can go from profitable to non-profitable real quick with ads. This will determine whether your company is around a ye...
Voice and Language Tech // Catherin Breslin // Coffee Sessions #129
October 21, 2022 12:37 - 49 minutes - 45.8 MBMLOps Coffee Sessions #129 {Podcast BTS} with Catherin Breslin, Voice and Language Tech co-hosted by Adam Sroka. // Abstract Back in the day, Speech Recognition was its own thing. It's a very different flavor of Data Science. You could not use a lot of the tools. It wouldn't cross over to this type of machine learning. Now, with the advancements, Speech Recognition and Machine learning are coming in together. It's interesting to hear right from someone with a Ph.D. level working with some...
Managing Machine Learning Projects // Simon Thompson // MLOps Coffee Sessions #128
October 19, 2022 11:23 - 45 minutes - 41.2 MBMLOps Coffee Sessions #128 with Simon Thompson, Managing Machine Learning Projects co-hosted by Abi Aryan. // Abstract It's a cliche to say that choosing and running the algorithms is only a small part of a typical ML project but despite that it's true! Setting up and organizing the project, dealing with the data asset, getting to the heart of the business problem, assessing and choosing the models, and integrating them with the business processes in production are all at least as time-con...
Reliable ML // Niall Murphy & Todd Underwood // Coffee Sessions #127
October 07, 2022 12:20 - 1 hour - 57.1 MBMLOps Coffee Sessions #127 with Niall Murphy & Todd Underwood, Reliable ML co-hosted by David Aponte. // Abstract By applying an SRE mindset to machine learning, authors and engineering professionals Cathy Chen, Kranti Parisa, Niall Richard Murphy, D. Sculley, Todd Underwood, and featured guest authors show you how to run an efficient and reliable ML system. Whether you want to increase revenue, optimize decision-making, solve problems, or understand and influence customer behavior, you'll...
ML Unicorn Start-up Investor Tells-IT-All // George Mathew // MLOps Coffee Sessions #126
October 04, 2022 13:30 - 51 minutes - 46.7 MBMLOps Coffee Sessions #126 with George Mathew, ML Unicorn Start-up Investor Tells-IT-All. // Abstract What's so enticing about enterprise software? It's incredible to see George's idea and vision to invest in generationally enduring companies. Let's look at the way how George likes to structure deals with companies while he's reviewing them and let's look at the MLOps ecosystem through the eyes of the investors. // Bio George Mathew joins Insight Partners as a Managing Director focu...
Databricks Model Serving V2 // Rafael Pierre // Coffee Sessions #125
September 30, 2022 11:16 - 55 minutes - 50.7 MBMLOps Coffee Sessions #125 with Rafael Pierre, Deploying Real-time ML Models in Minutes with Databricks Model Serving V2 co-hosted by Ryan Russon. // Abstract From our experience helping customers in the Data and AI field, we learned that the most challenging part of Machine Learning is deploying it. Putting models into production is complex and requires additional pieces of infrastructure as well as specialized people to take care of it - this is especially true if we are talking about r...
Monitoring Unstructured Data // Aparna Dhinakaran & Jason Lopatecki // Lightning Sessions #2
September 27, 2022 11:42 - 10 minutes - 9.83 MBLightning Sessions #2 with Aparna Dhinakaran, Co-Founder and Chief Product Officer, and Jason Lopatecki, CEO and Co-Founder of Arize. Lightning Sessions is sponsored by Arize // Abstract Monitoring embeddings on unstructured data is not an easy feat let's be honest. Most of us know what it is but don't understand it one hundred percent. Thanks to Aparna and Jason of Arize for breaking down embedding so clearly. At the end of this Lightning talk, we get to see a demo of how Arize deals...
Trustworthy Machine Learning // Kush Varshney // Coffee Sessions #124
September 21, 2022 10:29 - 58 minutes - 53.8 MBMLOps Coffee Sessions #124 with Kush Varshney, Distinguished Research Staff Member and Manager IBM Research, Trustworthy Machine Learning co-hosted by Krishnaram Kenthapadi. // Abstract Trustworthy ML is a way of thinking and something to be worked on and operationalized throughout the entire machine learning development lifecycle, starting from the problem specification phase that should include diverse stakeholders. // Bio Kush R. Varshney was born in Syracuse, New York in 1982. He r...
Trustworthy Machine Learning // Kush Varshney // Coffee Sessions #125
September 21, 2022 10:29 - 58 minutes - 53.8 MBMLOps Coffee Sessions #124 with Kush Varshney, Distinguished Research Staff Member and Manager IBM Research, Trustworthy Machine Learning co-hosted by Krishnaram Kenthapadi. // Abstract Trustworthy ML is a way of thinking and something to be worked on and operationalized throughout the entire machine learning development lifecycle, starting from the problem specification phase that should include diverse stakeholders. // Bio Kush R. Varshney was born in Syracuse, New York in 1982. He r...
RECOMMENDER SYSTEM: Why They Update Models 100 Times a Day // Gleb Abroskin // MLOps Coffee Sessions #123
September 16, 2022 17:45 - 52 minutes - 47.7 MBMLOps Coffee Sessions #123 with Gleb Abroskin, Machine Learning Engineer at Funcorp, RECOMMENDER SYSTEM: Why They Update Models 100 Times a Day co-hosted by Jake Noble. // Abstract FunCorp was a top 10 app store. It was a very popular app that has a ton of downloads and just memes. They need a recommendation system on top of that. Memes are super tricky because they're user-generated and they evolve very quickly. They're going to live and die by the Recommender System in that product. It'...
How & Why They Update Models 100 Times a Day at Funcorp // Gleb Abroskin // MLOps Coffee Sessions #123
September 16, 2022 17:45 - 52 minutes - 47.7 MBMLOps Coffee Sessions #123 with Gleb Abroskin, Machine Learning Engineer at Funcorp, How & Why We Update Models 100 Times a Day at Funcorp co-hosted by Jake Noble. // Abstract FunCorp was a top 10 app store. It was a very popular app that has a ton of downloads and just memes. They need a recommendation system on top of that. Memes are super tricky because they're user-generated and they evolve very quickly. They're going to live and die by the Recommender System in that product. It's inc...
Scaling Similarity Learning at Digits // Hannes Hapke // Coffee Sessions #122
September 09, 2022 13:50 - 57 minutes - 53 MBMLOps Coffee Sessions #122 with Hannes Hapke, Machine Learning Engineer at Digits Financial, Inc., Scaling Similarity Learning at Digits co-hosted by Vishnu Rachakonda. // Abstract Machine Learning in a product is a double-edged sword. It can make a product more useful but it depends on assumed and strictly defined behavior from users. Hannes walks through the entirety of their machine learning pipeline, how they implemented it, what the elements are, what the learning looks like, and w...
Bringing DevOps Agility to ML// Luis Ceze // Coffee Sessions #121
September 06, 2022 11:24 - 1 hour - 59.8 MBMLOps Coffee Sessions #121 with Luis Ceze, CEO and Co-founder of OctoML, Bringing DevOps Agility to ML co-hosted by Mihail Eric. // Abstract There's something about this idea where people see a future where you don't need to think about infrastructure. You should just be able to do what you do and infrastructure happens. People understand that there is a lot of complexity underneath the hood and most data scientists or machine learning engineers start deploying things and shouldn't ha...
Feathr: LinkedIn's High-performance Feature Store // David Stein // Coffee Sessions #120
September 02, 2022 10:04 - 53 minutes - 49.7 MBMLOps Coffee Sessions #120 with David Stein, Senior Staff Software Engineer at LinkedIn, Feathr: LinkedIn's Enterprise-Grade, High-Performance Feature Store co-hosted by Skylar Payne. // Abstract When David started building Feathr, Feature Stores did not exist. That was not a term floating around at all. This was definitely one of the OG Feature Stores for sure! We hear how the LinkedIn team got to this point, having an open source release, and how they used LinkedIn as an incubator to ...
MLOps at DoorDash // Hien Luu and DoorDash Leads // Coffee Sessions #119
August 30, 2022 10:29 - 45 minutes - 42.3 MBMLOps Coffee Sessions #119 with Hien Luu, Sr. Engineering Manager of DoorDash, MLOps at DoorDash: 3 Principles for Building an ML Platform That Will Sustain Hypergrowth co-hosted by Skylar Payne. // Abstract Machine Learning plays a big part at DoorDash in terms of what they do on a daily basis. It powers many of their core infrastructures. When it comes to DoorDash's business, they have to be leveraging machine learning and it is such a huge piece of the business that it is critical. ...
ML Platforms, Where to Start? // Olalekan Elesin // Coffee Sessions #118
August 26, 2022 13:30 - 53 minutes - 49.1 MBMLOps Coffee Sessions #118 with Olalekan Elesin, Director of Data Platform & Data Architect at HRS Product Solutions GmbH, co-hosted by Vishnu Rachkonda. // Abstract You don't have infinite resources? Call out your main metrics! Focus on the most impactful things that you could do for your data scientists. Olalekan joined us to talk about his experience previously building a machine learning platform at Scaleout24. From our standpoint, this is the best demonstration and explanation of...
Data Engineering for ML // Chad Sanderson // Coffee Sessions #117
August 19, 2022 11:28 - 58 minutes - 53.9 MBMLOps Coffee Sessions #117 with Chad Sanderson, Head of Product, Data Platform at Convoy, Data Engineering for ML co-hosted by Josh Wills. // Abstract Data modeling is building relationships between core concepts within your data. The physical data model shows how the relationships manifest in your data environment but then there's the semantic data model, the way that entity relationship design is extracted away from any data-centric implementation. Let's do the good old fun of talkin...
Scaling Machine Learning with Data Mesh // Shawn Kyzer // Coffee Sessions #116
August 17, 2022 12:26 - 54 minutes - 50 MBMLOps Coffee Sessions #116 with Shawn Kyzer, Principal Data Engineer at Thoughtworks (Spain), Scaling Machine Learning with Data Mesh co-hosted by Adam Sroka. // Abstract You can't just get something done by using tools. You need to go much deeper than that and it is very clear that Data Mesh is the same thing. You have to educate the organization about the movement. In this session, Shawn broke down the cultural piece of data mesh and how many parallels there are with the MLOps Moveme...
How Hera is an Enabler of MLOps Integrations // Flaviu Vadan // Coffee Sessions #115
August 14, 2022 12:29 - 41 minutes - 38.8 MBMLOps Coffee Sessions #115 with Flaviu Vadan, Senior Software Engineer at Dyno Therapeutics, How Hera is an Enabler of MLOps Integrations co-hosted by Vishnu Rachakonda. // Abstract Flaviu talks about the internal ML platform at Dyno Therapeutics called Hera. His team uses Hera as an internal innovation engine to help discover new breakthroughs with machine learning in the biotech healthcare industry. / Bio Flaviu is a Senior Software Engineer at Dyno Therapeutics, the leading organizati...
Product Enrichment and Recommender Systems // Marc Lindner and Amr Mashlah // Coffee Sessions #114
August 10, 2022 12:18 - 56 minutes - 52.4 MBMLOps Coffee Sessions #114 with Marc Lindner, Co-Founder COO and Amr Mashlah, Head of Data Science of eezylife Inc., Product Enrichment and Recommender Systems co-hosted by Skylar Payne. // Abstract The difficulties of making multi-modal recommender systems. How it can be easy to know something about a user but very hard to know the same thing about a product and vice versa? For example, you can clearly know that a user wants an intellectual movie, but it is hard to accurately classify a ...
Building Better Data Teams // Leanne Fitzpatrick // Coffee Sessions #113
August 06, 2022 11:42 - 1 hour - 57.4 MBMLOps Coffee Sessions #113 with Leanne Fitzpatrick, Director of Data Science of Financial Times, Building Better Data Teams co-hosted by Mihail Eric. // Abstract We spent a lot of time talking about data tooling but we maybe spent not as much time talking about data organizations and efficiently running and organizing data teams. What about starting with limitations instead of aspirations? Right constraints instead of the north star? In this session, let's learn more about a realistic...
MLflow Pipelines: Opinionated ML Pipelines in MLflow // Xiangrui Meng // Coffee Sessions #112
August 03, 2022 13:40 - 50 minutes - 46.5 MBMLOps Coffee Sessions #112 with Xiangrui Meng, Principal Software Engineer of Meng, MLX: Opinionated ML Pipelines in MLflow co-hosted by Vishnu Rachakonda. // Abstract MLflow Pipelines enable data scientists to stay mostly within their comfort zone utilizing their expert knowledge while following the best practices in ML development and delivering production-ready ML projects, with little help from production engineers and DevOps. // Bio Xiangrui Meng is a Principal Software Engineer at ...
MLX: Opinionated ML Pipelines in MLflow // Xiangrui Meng // Coffee Sessions #112
August 03, 2022 13:40 - 50 minutes - 46.5 MBMLOps Coffee Sessions #112 with Xiangrui Meng, Principal Software Engineer of Databricks, MLX: Opinionated ML Pipelines in MLflow co-hosted by Vishnu Rachakonda. // Abstract MLX is to enable data scientists to stay mostly within their comfort zone utilizing their expert knowledge while following the best practices in ML development and delivering production-ready ML projects, with little help from production engineers and DevOps. // Bio Xiangrui Meng is a Principal Software Engineer at D...
More than a Cache: Turning Redis into a Composable, ML Data Platform // Samuel Partee // Coffee Sessions #111
July 30, 2022 12:14 - 48 minutes - 44.9 MBMLOps Coffee Sessions #111 with Samuel Partee, Principal Applied AI Engineer of Redis, More than a Cache: Turning Redis into a Composable, ML Data Platform co-hosted by Mihail Eric. This episode is sponsored by Redis. // Abstract Pushing forward the Redis platform to be more than just the web-serving cache that we've known it up to now. It seems like a natural progression for the platform, we see how they're evolving to be this AI-focused, AI native serving platform that does vector simila...
Just Fetch the Data and then... // David Bayliss // Coffee Sessions #110
July 29, 2022 11:14 - 52 minutes - 48.2 MBMLOps Coffee Sessions #110 with David Bayliss, Chief Data Scientist of LexisNexis Risk Solutions, Just Fetch the Data and then... co-hosted by Vishnu Rachakonda. // Abstract Composing data to extract features can be a significant problem. Key factors are the data size, compliance restrictions, and real-time data. Ethics (and law) can drive extremely complex audit requirements. In the cloud, you can do anything - at a price. // Bio One of the creators of the world's first big data platfor...
Just Fetch the Data and then... // David Bayliss // Coffee Sessions #110
July 28, 2022 12:04 - 52 minutes - 48.2 MBMLOps Coffee Sessions #110 with David Bayliss, Chief Data Scientist of LexisNexis Risk Solutions, Just Fetch the Data and then... co-hosted by Vishnu Rachakonda. // Abstract Composing data to extract features can be a significant problem. Key factors are the data size, compliance restrictions, and real-time data. Ethics (and law) can drive extremely complex audit requirements. In the cloud, you can do anything - at a price. // Bio One of the creators of the world's first big data platfor...
Why You Need More Than Airflow // Ketan Umare // Coffee Sessions #109
July 23, 2022 11:35 - 1 hour - 66.3 MBMLOps Coffee Sessions #109 with Ketan Umare, Co-founder and CEO of Union.ai, Why You Need More Than Airflow co-hosted by George Pearse. // Abstract Airflow is a beloved tool by data engineers and Machine Learning Engineers alike. But when doing ML what are the shortcomings and why is an orchestration tool like that not always the best developer experience? In this episode, we break down what some key drivers are for using an ML-specific orchestration tool. // Bio Ketan Umare is the CEO a...
ML Flow vs Kubeflow 2022 // Byron Allen // Coffee Sessions #108
July 19, 2022 13:34 - 1 hour - 61.1 MBMLOps Coffee Sessions #108 with Byron Allen, AI & ML Practice Lead at Contino, ML Flow vs Kubeflow 2022 co-hosted by George Pearse. // Abstract The amazing Byron Allen talks to us about why MLflow and Kubeflow are not playing the same game! ML flow vs Kubeflow is more like comparing apples to oranges or as he likes to make the analogy they are both cheese but one is an all-rounder and the other a high-class delicacy. This can be quite deceiving when analyzing the two. We do a deep dive ...
Why and When to Use Kubeflow for MLOps // Ryan Russon // Coffee Sessions #107
July 11, 2022 10:22 - 58 minutes - 54.5 MBMLOps Coffee Sessions #107 with Ryan Russon, Manager, MLOps and Data Science of Maven Wave Partners, Why and When to Use Kubeflow for MLOps co-hosted by Mihail Eric. // Abstract Kubeflow is an excellent platform if your team is already leveraging Kubernetes and allows for a truly collaborative experience. Let’s take a deep dive into the pros and cons of using Kubeflow in your MLOps. // Bio From serving as an officer in the US Navy to Consulting for some of America's largest corporat...
Building a Culture of Experimentation to Speed Up Data-Driven Value // Delina Ivanova // MLOps Coffee Sessions #106
July 05, 2022 11:29 - 54 minutes - 50.1 MBMLOps Coffee Sessions #106 with Delina Ivanova, Associate Director, Data of HelloFresh, Building a Culture of Experimentation to Speed Up Data-Driven Value co-hosted by Vishnu Rachakonda. // Abstract Supply chain/manufacturing are prime areas where the use of data science/analytics/ ML is underdeveloped, and experimentation is required to collect data and enable data-driven solutions. This talk encourages companies to conduct experiments and collect data over time in order to build accura...
Cleanlab: Labeled Datasets that Correct Themselves Automatically // Curtis Northcutt // MLOps Coffee Sessions #105
July 01, 2022 09:30 - 1 hour - 61.2 MBMLOps Coffee Sessions #106 with Curtis Northcutt, CEO & Co-Founder of Cleanlab, Cleanlab: Labeled Datasets that Correct Themselves Automatically co-hosted by Vishnu Rachakonda. // Abstract Pioneered at MIT by 3 Ph.D. Co-Founders, Cleanlab is an open-source/SaaS company building the premier data-centric AI tools workflows for (1) automatically correcting messy data and labels, (2) auto-tracking of dataset quality over time, (3) automatically finding classes to merge and delete, (4) auto ml ...